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What is the numpy.sign() function in NumPy?

Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

Overview

The sign() function in NumPy is used to return the sign of each element (numbers) of an array.

Syntax

numpy.sign(x, /, out=None, *, where=True)

Parameter value

The sign() function takes the following parameter values:

  • x : The input array of values. It is a required parameter.
  • out : The location where the result is stored. It is an optional parameter.
  • where : This is the condition over which the input is broadcast. At a given location where this condition is True, the resulting array will be set to the ufunc result. Otherwise, the resulting array will retain its original value. It is an optional parameter.
  • **kwargs : This is the other keyword argument. It is an optional parameter.

Return value

The sign() function returns an array of the same shape as the input array passed to it, holding the sign of values of the elements of the input array.

-1 is returned if the number is less than 0. 1 is returned for numbers greater than 0. 0 is returned if the number is equal to 0. NaN is returned if the input is a NaN.

Code example

Let's look at the code below:

import numpy as np
# creating an input array of complex values
x = np.array([-1, 6, -2.5, 2])
# implementing the sign() function
myarray = np.sign(x)
print(x)
print(myarray)
Implementing the sign() function

Code explanation

  • Line 1: We import the numpy module.
  • Line 4: We create an array x using the array() function.
  • Line 7: We implement the sign() function on the input array. We assign the result to a variable myarray.
  • Line 9: We print the variable x.
  • Line 10: We print the variable myarray.

RELATED TAGS

function
numpy
python
communitycreator

CONTRIBUTOR

Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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